This dissertation studies small- and medium- scale enterprises’ (SMEs) transactions on online Business-to-Business (B2B) platforms and their implications using secondary data obtained from a platform. The motivation for the dissertation comes from over two years of field visits and weekly meetings with platform managers, which revealed differences between users of B2B and B2C/P2P platforms that are explored in the literature. The first chapter titled Ranking Quality and User Engagement on an Online B2B Platform’ studies how the browsing behavior of B2B users changes in response to a continuously improving recommendation system. Online B2B platforms are increasingly investing in data science teams to develop machine-learning algorithms to provide personalized rankings-based user recommendations. These algorithms continuously evolve over time due to frequent innovations by data scientists and dynamic learning of weights from users’ recent activity. Thus, there is a growing need to develop ways to monitor the performance of these algorithms over time. The chapter answers two key questions faced by platforms: (i) how to periodically measure the quality of rankings presented to the user using real-time ranked transactions data and, (ii) what is the effect of improving ranking quality on usage (i.e., the number of transactions) and browsing effort of the user. I propose methods to measure ranking quality, develop a position-level model of a user’s decision to transact and scroll, and develop estimation approaches to overcome censoring. The second chapter titled The Democratization Effect of Online B2B Platforms' studies if B2B platforms help SMEs overcome the distance barrier for geographic expansion. Efforts to onboard SMEs to e-commerce to achieve a “single market” are ongoing globally. For example, Amazon introduced European Expansion Accelerator to enable SMEs to sell in nine countries and Unilever is onboarding micro- and nano-stores in rural India to B2B platforms. These efforts typically assume that SMEs leverage B2B platforms for geographic expansion. However, various frictions—such as trust deficits, limited access to capital, and distance—may impede expansion, making it an empirical question whether SMEs actually use B2B platforms to expand geographically. Using a gravity model with network specific error structure, this chapter finds that SMEs do indeed utilize B2B platforms for geographic expansion. The final chapter focuses on how to generate network effects on B2B platforms. Network effects on P2P/B2C platforms are typically considered in terms of single-link interactions between two sides of a market. For example, how does increasing the number of job posters on an online labor platform affect the number of job seekers on the platform and vice versa? However, users of B2B platforms are often both buyers of an upstream commodity (e.g. rubber) and sellers of a downstream commodity (e.g. tires). This means multiple single-link interactions are uniquely connected through the supply chain network on B2B platforms. Consequently, there is a possibility of increasing the number of sellers of an upstream product by increasing the number of buyers of a downstream product. Preliminary results using simultaneous equations with instruments indicate this possibility.